EDBT 2026 Demo / reviewers in the wild / expert
Daito Mutsuo
dblp:44/1253
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Robot manipulation · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
grasping |
0.0 | 1 | 2001 | Optimization of Power Grasps for Multiple Objects · ICRA 2001 |
Robotics › Robot manipulation › grasping › multifingered grasping
power grasp |
0.0 | 1 | 2001 | Optimization of Power Grasps for Multiple Objects · ICRA 2001 |
Robotics › Robot manipulation › grasping
grasp optimization |
0.0 | 1 | 2001 | Optimization of Power Grasps for Multiple Objects · ICRA 2001 |
Methods — techniques the papers use, named apart from their topics
numerical simulation · 0.0joint torque optimization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Optimization of Power Grasps for Multiple ObjectsabstractPower grasp is a grasp that can hold objects stably without changing the joint torques of fingers. Almost all studies on power grasp deal with one object, but it is more efficient to hold multiple objects at the same time. This paper derives a condition for power grasp for multiple objects, and defines an optimal power grasp from the viewpoint of decreasing the work of joint torques. Finally, we show some numerical examples to verify the validity of our approach. Tsuneo Yoshikawa, Tetsuyou Watanabe, Daito Mutsuo |
ICRA | 3 |